Research for Accuracy

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November 1, 1994
In 1991, the Department of Defense revised its instructions governing defense acquisition management. The role of Cost and Operational Effectiveness Analyses (COEAs) was spelled out at length. COEAs must be completed and presented to the acquisition decision executives at key decision milestones. For major acquisition programs, the analyses undergo extensive review within the military departments and in the Office of the Secretary of Defense. Thus, COEAs are primary--although not the only--means by which the decision authorities become informed about a program's advantages and disadvantages. Since 1991, CNA has provided leadership and staffing for a number of COEAs for the Navy and Marine Corps. Moreover, CNA has conducted COEA-like studies for various components of the Department of the Navy for many years. This paper, which draws from the collective experience of that work as well as from longer-standing principles of defense systems analysis, identifies and discusses certain issues that appear to be common to all COEAs. Each issue relates in some way to the use or misuse of cost information in the analysis. We begin with an overview of the role of COEAs in the acquisition process and a general discussion of the objectives of these studies and how they are put together. We then focus on the following issues: system versus decision alternatives; integrating cost and effectiveness results; wartime costs; discounting; risk and uncertainty analysis; and affordability.
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July 1, 1994
One of the inherent features of the Medical Expense and Performance Reporting System (MEPRS) is the use of the DoD composite standard military rates as an estimate of military labor. The composite rates essentially give an average salary by paygrade. Our purpose in this analysis is to determine: (a) How well MEPRS approximates total military physician compensation in comparison to other non-medical corps officers; and (b) Whether the use of the composite rates introduces any bias to estimates of costs associated with providing types of specialty care.
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December 1, 1993
The focus of this paper, which draws liberally from an earlier CNA paper that also employed Monte Carlo methods, is on the predictive accuracy of cost-estimating relationships whose parameters are estimated by both ordinary least squares regression and non-linear least squares, first when the error structure is known to be multiplicative and then when it is known to be additive. The multi-predictor model that served as the basis of the Monte Carlo simulations is representative of models that cost analysts frequently deal with. Results suggest that predictions based on non-linear least squares are substantially better than those based on ordinary least squares when the errors are additive, and are only slightly inferior when the error term is multiplicative.
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June 1, 1993
This paper reports on a Monte Carlo study of the accuracy of each estimation method under correct and incorrect error specifications. The multi-predictor model that serves as the basis of the study is representative of models with which cost analysts frequently deal. Results suggest that ordinary least squares, applied to the logs of the variables, may be the preferred method under either specification. This finding, however, is applicable strictly to the issue of parameter estimation. Accuracy of cost prediction requires further analysis.
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July 1, 1992
The Armed Services Vocational Aptitude Battery (ASVAB), used to select and classify enlisted personnel, is highly correlated to math and verbal content areas. New computerized predictor tests that are sensitive to traits not measured by the current ASVAB subtests may be able to improve predictive validity. This research memorandum investigates the potential of one such group of tests, the Enhanced Computer-Administered Tests, to predict performance in the mechanical maintenance specialties.
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September 1, 1991
The Defense Department developed a Computerized Adaptive Testing (CAT) version of the Armed Services Vocational Aptitude Battery (ASVAB). During the Mechanical Maintenance phase of the Marine Corps Job Performance Measurement (JPM) project, CAT-ASVAB was administered to over 1,400 Marines in Automotive Repair and Helicopter Repair occupations. The scores of these Marines were analyzed to assess the reliability of CAT-ASVAB, the potential effects of test item compromise, and how the use of computers has affected the nature of speed tests. This research memorandum presents the results of the analysis.
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May 1, 1988
This research memorandum documents the Center for Naval Analyses' assessment of the Price Waterhouse shore base facility condition readiness model. The accuracy and reasonableness of the model's predictions are assessed. Suggestions are made for revising the presentation of the model's results and for refining the model.
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February 1, 1988
Navy Enlisted Classification (NEC) codes identify an individual's particular skills in more detail than the Navy occupational or rating structure. This research memorandum summarizes an analysis to determine the timeliness of the NEC reports to the Enlisted Master Record(EMR). Using quarterly EMR files from June 1983 to June 1984 and from June 1986 to June 1987, analysts estimated the NEC reporting lags (i.e., time between the date the NEC is awarded and the date the NEC is posted to an individual's EMR record). The results indicate that NEC reporting lags are relatively rare. Over 90 percent of the NECs appeared on the quarterly EMR within four months of their being awarded. Looking ahead only one quarter, therefore, seems to be sufficient for achieving a relatively complete count, whether one is estimating the number of new awards or determining the total count.
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April 1, 1980
This objectives of this paper are to calculate the probability that a given ship in a formation is targeted by a given number of incoming ASMs, and to calculate the probability that a given ship will survive the raid.
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March 1, 1978

This paper presents tables and graphs assessing the accuracy of a formula (programmable on a desk calculator) for approximating the circular coverage function of a circular-normal probability distribution. Use of this formula together with the error curves presented here enable one to calculate the circular coverage function with a maximum error on the order of 0.0002 for offsets up to 50 and covering-circle radii up to 4.50.

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